1. Field of the Invention
The present invention relates to a method for controlling location distribution of sensing node, selection for sensing node, format design of sensing implementation and a procedure performing spectrum sensing in cognitive radio networks. Specifically, the invention relates to an efficient and reliable method that aims at minimizing time overhead consumed during spectrum sensing with open wireless architecture (OWA).
2. Related Arts
Present wireless services are often provided by following the fixed allocation of radio spectrum. This leads to the low spectrum utilization efficiency. Currently, the service providers are faced with a situation where they require a larger amount of spectrum to satisfy the increasing quality of service (QoS) requirements of the users. An efficient method for alleviating the problem is to adopt cognitive spectrum access. Spectrum sensing should be designed for performing measurements on a part of the spectrum and making a decision related to spectrum usage based upon the measured condition of the spectrum.
This has fostered the researches in unlicensed spectrum access, and spectrum sensing has been seen as an important enabler for this. In a scenario in which there exists a licensed user (primary user), any unlicensed (secondary) user needs to ensure that the primary user is protected, i.e., that no secondary user is harmfully interfering any primary user operation. Spectrum sensing can be used to detect the presence (or absence) of a primary user. Recently, FCC (federal communications commission) regulations have paved way for utilizing spectrum obtained from unused TV (television) channels, the so-called TV white spaces. In these regulations, spectrum sensing plays a major role.
Cognitive radio spectrum access is a feasible and powerful manner for solving the spectrum usage problem. Such radio devices should be capable of sensing spectrum occupancy, and, in conformity with the rules of the FCC, opportunistically adapting transmission to utilize empty frequency bands without disrupting primary user systems. However, this departure from traditional license-based spectrum allocation policies could disrupt existing systems if the spectrum utilization decision is based on unreliable spectral estimation.
Spectrum sensing as the focus of the present invention is the most important part for the establishment of cognitive radio link of wireless cellular networks or wireless access networks as secondary user system. This sensing task, often referred to as spectrum sensing, is a major aspect of cognitive radio and has the important effect on the spectrum utilization efficiency. Spectrum sensing is to achieve awareness about the spectrum usage and existence of primary users in a geographical area. This awareness can be obtained by using geolocation and database, or by local spectrum sensing at cognitive radios. There are some other solutions that can be thought of as alternatives, or complements, to spectrum sensing, such as using a database of (licensed) spectrum usage, which can be queried for spectrum opportunities, or advertising spectrum opportunities over a Cognition enabling Pilot Channel (CPC) as developed in the E2R (End-to-End Reconfigurability) and E3 (End-to-End Efficiency) projects of European Commission and in RRS (Reconfigurable Radio Systems) of ETSI (European Telecommunications Standards Institute).
Although it is possible to realize the unlicensed spectrum access by capturing the efficient spectrum opportunities, a problem arises due to the difficulty in obtaining both the accuracy of spectrum sensing and the minimization of the related time overhead. This is particularly critical when considering the mobility of sensing node having the limited hardware resource. In addition, since the complexity increases as the number of sensing nodes increases, a compromise should be pursued in sensing process that takes both the number of sensing node and the accuracy of sensing result into account.
One possible approach to increase the spectral estimation reliability and decrease the probability of interference of cognitive radios to existing radio systems is by spectrum sensing. In such a distributed approach, the spectrum occupancy is determined by the joint sensing of multiple cognitive radio nodes, instead of being determined individually by each cognitive radio node.
In application scenarios involving geographically distributed radios, such as a wireless cellular system, distributed spectrum sensing approaches are worth considering due to the variability of the radio signal. Such methods can efficiently increase the reliability of the spectrum estimation process, at the expense of computational complexity and power/bandwidth usage for the transmission of spectrum sensing information.
Being a key enabling functionality in cognitive radio networks, spectrum sensing needs to reliably detect weak primary radio (PR) signals of possibly-unknown types. Spectrum sensing should be cable of monitoring the activation of primary users in order for the secondary users to vacate the occupied spectrum segments. However, it is difficult for a cognitive radio to capture such information instantaneously due to the absence of cooperation between the primary and secondary users. Thus, recent research efforts on spectrum sensing have focused on the detection of ongoing primary transmissions by cognitive radio devices. Generally, radio spectrum detection methods fall into three categories: energy detection, coherent detection, and cyclostationary feature detection.
If the secondary user has limited information on the primary signals (e.g., only the local noise power is known), then the energy detector is optimal. When certain primary signal features are known to the cognitive radios (CRs) (such as pilots, preambles, or synchronization messages), the optimal detector usually applies the matched filter structure to maximize the probability of detection. Additionally, cyclostationary feature detectors differentiate the primary signal energy from the local noise energy by exploiting certain periodicity exhibited by the mean and autocorrelation of a particular modulated signal.
Regardless of primary signal features, it is necessary for secondary user system to obtain the accurate and reliable occupancy of the spectrum utilization while the resource overhead used during sensing can be minimized. In wireless cellular networks, spectrum sensing can be realized by either base station (BS) or by mobile users with mobile devices. The reliable sensing process can be achieved by BS due to its powerful hardware resource and computation ability. However, the fixed location of BS can not always guarantee the higher reliability of sensing results because wireless signal energy fades as the transmission distance increases. Primary user node has the randomness in both the location distribution and the condition of service link, which makes it more difficult to efficiently and reliably obtain the occupancy of the spectrum. By considering both the difficulties in sensing process and the fixed sensing ability of mobile user, the present invention aims at increasing the efficiency and reliability of sensing process by alleviating the effect caused by the randomness of both the location of spectrum utilization and the spectrum signal energy on the reliability of sensing result.
Schemes on user-cooperation for primary spectrum sensing are studied in [S. M. Mishra, et al, “Cooperative Sensing among Cognitive Radios,” in IEEE International Conference on Communications, ICC 2006, vol. 4, pp. 1658-1663, June 2006.] and [E. Visotsky, et al, “On Collaborative Detection of TV Transmissions in Support of Dynamic Spectrum Sharing,” in First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, DySPAN 2005, pp. 338-345, November 2005], where some kind of joint detection is utilized among all the cooperating users. Gathering the entire received data at one place is very difficult due to practical wireless communication constraints. In practice, cooperation between the cognitive radio users cannot always be feasible in general since a user can cooperate with others only when there are other users in its vicinity monitoring the same frequency band as itself. Another feasible system is the hard-decision strategy considered in [A. Ghasemi, et al, “Collaborative spectrum sensing for opportunistic access in fading environments,” in First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, DySPAN 2005, pp. 131-136, November 2005], where the individual secondary user independently makes decisions about the presence of the frequency band that are being monitored and transfer their decisions to a fusion center. The final decision about the occupancy of the band is made at the fusion center by fusing the decisions made by all cooperating users in that area that were monitoring the same frequency band.
In cooperating spectrum sensing, the fusion center has the centralized management function that controls the channel assignment and scheduling for the secondary users. It can be realized at the fusion center that the secondary users exchange their information including sensing decisions and geographic locations and the correlation between the observations.
Fusion of data observed at distributed locations is an integral part of any decentralized detection procedure. However, most of the significant works on decentralized detection have been tremendously limited on the cases with conditionally observations only. The correlated case has also been studied, but the results are often not very easy to implement in practice as described in [E. Drakopoulos, et al, “Optimum multisensor fusion of correlated local decisions,” IEEE Trans. Aerospace and Electronic Systems, vol. 27, no. 4, pp. 5-14, July 1991]. Since the cooperating secondary users are expected and limited to be located close to each other and are monitoring the same frequency band, the distributions of the received powers they see can be modeled as being identical, albeit not independent. So the problem now becomes a binary hypothesis testing problem to decide whether or not the received mean power at their location is higher than the power expected at the outer edge of the protected region.
Detecting a spectrum hole in a wideband spectrum involves two major challenges. First, the spectrum holes are spread across the wideband spectrum and their availability status changes rapidly. Therefore, the secondary users should be agile enough to detect the holes within a period considerably shorter than the entire duration of its vacancy. Secondly, in order to avoid harming the communication of the primary users, the secondary users must distinguish the holes from the channels occupied by the primary users reliably, irrespective of how weak the transmissions of the primary users are.
When designing spectrum sensing scheme that quickly and reliably realizes the spectrum sensing, irrespective of how weak the transmissions of the primary users are and how distributed the transmissions of the primary users spatially are, the adaptation to this must be satisfied in order to obtain the reliable sensing process while minimizing the time overhead consumed during spectrum sensing.
In addition, all of the aforementioned references are limited to the specific wireless standard or carrier only for the primary users, rather than supporting multiple wireless standards or different radio transmission technologies. Hence, the primary network of the aforementioned references is in closed wireless architecture.